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信源方位估计是阵列信号处理的一个重要问题。基于信源空间分布稀疏的本质,利用压缩传感理论,构造出一种稀疏信源方位估计模型,仿真结果表明,在不考虑噪声的理想情况和满足压缩传感的条件下,不仅可以准确的恢复出原始信源的方位,而且精确的得到各个信源信号的强度,并且,这种新的模型只需要一次时间采样,从而大大降低了成本。
Source orientation estimation is an important issue in array signal processing. Based on the sparse nature of the source space distribution, a sparse source orientation estimation model is constructed by using compressed sensing theory. The simulation results show that under the condition of not considering the noise and satisfying the compression sensing, not only accurate Restore the original source orientation, and accurately get the strength of each source signal, and, this new model only needs time sampling, thus greatly reducing the cost.